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The Yushigou area in North Qilian, which is a research hotspot of thr paleo-oceanic basin, is located at the tectonic zone between the Alashane block and the Qaidam block at the north margin of the Qinghai-Tibet Plateau. The tectonic setting and the tectonic evolution of early Caledon at North Qilian is controversial, between rifted basin and oceanic basin. Some scholars believe that the north Qilian formed the matured ocean and the trench-arc-basin system in the early Ordovician period, while others insist that it just continued its rift valley evolution. In this study, the Axiosmax X-ray Fluorescence Spectrometer was used to measure the content of major elements and the X-Series 2 Inductively Coupled Plasma-Mass Spectrometry to measure the content of the trace elements and REE of the siliceous rocks collected from North Qilian. The results show that the mean ratio of Al/(Al+Fe+Mn) is 0.56 and 0.60, Al/(Al+Fe) is 0.57 and 0.61, (La/Yb)SN is 0.89 and 1.2, δCeSN is 0.88 and 0.93 and δEuSN is 1.15 and 1.08, for samples collected from two sites at Yushigou, respectively. Chondritic Standardized REEs distribution plot is a LREEs enrichment pattern which shows an outstanding rightward decreasing tendency. This evidence indicates that the tectonic settings of the siliceous rocks associated with subduction complex in Yushigou have a tectonic background of archipelagic ocean, of which some parts are close or far from the continental margin or the surrounding sea basin.

In actual rental market, based on the inflation characteristics that the rental cost each period and purchase price of an equipment generally continue to rise as time goes, we propose online rental decision model with increasing price index. By using online algorithm, we first investigate optimal offline strategies, and then present deterministic optimal online strategy and its competitive ratio. Prom the view of improving competitive performance of online strategy, basing on the idea of risk control, we propose randomized online strategy and its competitive ratio; and strictly prove that this strategy is an only randomized optimal online strategy for this problem by using analysis technique of two person zero-sum game. Moreover, we further point out that the competitive performance of deterministic and randomized optimal strategies are declined as the purchasing price of the equipment and the price index increase, respectively. Finally, numerical analysis illustrates that when there is inflation, the optimal decision date is relatively advanced, but the competitive performance of online strategy decreases significantly. Thus, it shows that the changes of price index have a significant effect on online rental decision. [ABSTRACT FROM AUTHOR]

Based on the online learning character of weak aggregating algorithm (WAA), this paper explores its application to online portfolio selection, and considers the situation of making decision according to finite expert advices. The WAA is first applied to the expert strategies that invest only on one stock; then the single aggregating strategy (SAS) for online portfolio selection is obtained and the competitive performance of this strategy is analyzed, which shows SAS can pursue the best stock. In real investment decision-making, investors may choose several stocks to construct portfolios to invest, the WAA is further applied to the expert strategies that invest on different numbers of stocks; the mixture aggregating strategy (MAS) for online portfolio selection is then obtained; the conclusion that the cumulative gain MAS achieved is as large as that achieved by the best expert advice is proved. Numerical examples of long-period portfolios are provided to illustrate that SAS can achieve gain as well as the best stock; MAS can achieve gain as well as the best constant rebalanced portfolio (BCRP) strategy, and can obtain more when compared with universal portfolio (UP) strategy, which shows great competitive performance. [ABSTRACT FROM AUTHOR]

This paper deals with a portfolio selection problem in fuzzy environment in which returns and turnover rates of assets are represented by fuzzy variables. A fuzzy multiple criteria portfolio selection optimization model is proposed with the objectives to maximize the return and the skewness of portfolio, while the risk, the ambiguity and the fuzziness of portfolio are minimized. In the proposed model, the cardinality constraint, the bounds of constraints, the liquidity constraint and the diversification degree of portfolio are taken into consideration. A weighted max-min approach for fuzzy goal programming is employed to transform the proposed model into a single objective programming problem. Then, a genetic algorithm is designed for solutions. Finally, we use an empirical example to illustrate the practicability of our model and the efficiency of the designed algorithm. The results illustrate that our model is an effective approach for expressing investors' different investment intention and the designed algorithm is effective. [ABSTRACT FROM AUTHOR]

The return of the best constant rebalanced portfolio (BCRP) has exponential growth rate with time. It is a hot topic to research on-line sequential investment strategy that has the same growth rate as BCRP. Based on the on-line learning of linear function, we firstly present a new on-line portfolio selection strategy, where the linear coefficient is the middle of an interval. And the interval is related to price relative and the return. Using the relative entropy as the distance function of two portfolios, we further prove that the new on-line portfolio is universal. Finally, take experiment on several portfolios that consisted of two stocks or three stocks, and compare the new strategy with Cover's UP strategy. The results show that this new strategy can obtain better performance. Therefore, this paper provides a new method and basis for decision-making for on-line sequential investment, and thus has great practical significance. [ABSTRACT FROM AUTHOR]